Signal processing method and device for signal-to-noise improvement

ABSTRACT

A method and apparatus extract a signal component of a measured signal using one of two methods. If the signal component in the measured signal is a periodic signal with a certain well-defined peak-to-peak intensity value, upper and lower envelopes of the measured signal are determined and analyzed to extract said signal component of the measured signal. This signal component can further be used to calculate a desired parameter of the sample. The DC component of the signal is determined as the median value of the upper envelope, and the AC component is determined as the median value of the difference between the upper and lower envelopes. If the signal component of the measured signal is a periodic signal characterized by a specific asymmetric shape, a specific adaptive filtering is applied to the measured signal, resulting in the enhancement of the signal component relative to a noise component. This adaptive filtering is based on a derivative of the Gaussian Kernel having specific parameters matching the characteristics of the signal component.

FIELD OF THE INVENTION

[0001] This invention is generally in the field of signal-to-noiseimprovement techniques, and relates to a method and device forprocessing a periodic signal. The present invention is particularlyuseful in pulse oximeters or other non-invasive measurement devices fordetermining oxygen saturation and/or cardiac output.

BACKGROUND OF THE INVENTION

[0002] Signal processing is an intrinsic procedure of any measurementtechnique, and always requires sufficient signal-to-noise ratio toenable extraction of a signal component indicative of a desiredparameter from a noise component contained in the measured signal. Forexample, measurement techniques aimed at determining physiologicalparameters consist of detecting and analyzing a signal response, e.g.,light response, of a sample to the application of an external field,e.g., electromagnetic radiation, and typically require suitable signalprocessing to extract the signal component in the detected response.

[0003] Various techniques for non-invasive measurements of bloodparameters have been developed. One of such techniques is the so-called“bio-impedance technique” consisting of the following. A current sourceproduces an alternating current, which is applied to the body throughelectrodes, and voltage induced by this current passage through the bodyis measured at additional electrodes. Other techniques utilizespectrophotometry consisting of illumination of a body part by incidentlight of various wavelengths and measurement of an absorption spectrum.

[0004] The most popular spectrophotometric techniques are oximetry andpulse oximetry. Oximetry is based on the strong dependence of theoptical property of blood in the visible (between 500 and 700 nm) andnear-infrared (between 700 and 1000 nm) spectra on the amount of oxygenin blood. Pulse oximetry, which utilizes transmission and reflectionmodes, relies on the detection of a photoplethysmographic signal causedby variations in the quantity of arterial blood associated with periodiccontraction and relaxation of a patient's heart. The magnitude of thissignal depends on the amount of blood ejected from the heart into theperipheral vascular bed with each systolic cycle, the optical absorptionof the blood, absorption by skin and tissue components, and the specificwavelengths that are used to illuminate the tissue. Oxyhemoglobinsaturation (SaO₂) is determined by computing the relative magnitudes ofred (R) and infrared (IR) photoplethysmograms.

[0005] Electronic circuits, or suitable software (algorithm) inside thepulse oximeter, separate the R and IR photoplethysmograms into theirrespective pulsatile (AC) and non-pulsatile (DC) signal components. Analgorithm inside the pulse oximeter performs a mathematicalnormalization by which the time-varying AC signal at each wavelength isdivided by the corresponding time-invariant DC component which resultsmainly from the light absorbed and scattered by the bloodless tissue,residual arterial blood when the heart is in diastole, venous blood andskin pigmentation. Since it is assumed that the AC portion results onlyfrom the arterial blood component, this scaling process provides anormalized R/IR ratio, i.e., the ratio of AC/DC values corresponding toR- and IR-spectrum wavelengths, respectively, which is highly dependenton SaO₂, but is largely independent of the volume of arterial bloodentering the tissue during systole, skin pigmentation, skin thicknessarid vascular structure.

[0006] Pulse oximetry operating in reflection mode, while being based onsimilar spectrophotometric principles as that of transmission mode, ismore challenging to perform and has unique problems that cannot alwaysbe solved by solutions suitable for solving the problems associated withtransmission-mode pulse oximetry. Generally, when comparing transmissionand reflection pulse oximetry, the problems associated with reflectionpulse oximetry consist of the following. In reflection pulse oximetry,the pulsatile AC signals are generally very small and, depending onsensor configuration and placement, have larger DC components ascompared to those of transmission pulse oximetry. In addition to opticalabsorption and reflection due to blood, the DC signal of the R and IRphotoplethysmograms in reflection pulse oximetry can be adverselyaffected by strong reflections from a bone. This problem becomes moreapparent when applying measurements at such body locations as theforehead and the scalp, or when the sensor is mounted on the chest overthe ribcage. Similarly, variations in contact pressure between thesensor and the skin can cause larger errors in reflection pulse oximetry(as compared to transmission pulse oximetry) since some of the bloodnear the superficial layers of the skin may be normally displaced awayfrom the sensor housing towards deeper subcutaneous structures.Consequently, the highly reflective bloodless tissue compartment nearthe surface of the skin can cause significant errors even at bodylocations where the bone is located too far away to influence theincident light generated by the sensor.

[0007] Another problem with reflectance sensors currently available isthe potential for specular reflection caused by the superficial layersof the skin, when an air gap exists between the sensor and the ski, orby the direct shunting of light between the LEDs and the photodetectorthrough a thin layer of fluid (which may be due to excessive sweating orfrom amniotic fluid present during delivery).

[0008] It is important to keep in mind the two fundamental assumptionsunderlying conventional dual-wavelength pulse oximetry: The path oflight rays with different illuminating wavelengths in tissue aresubstantially equal, and therefore, cancel each other. Each light sourceilluminates the same pulsatile change in arterial blood volume.Furthermore, the correlation between optical measurements and tissueabsorption in pulse oximetry are based on the fundamental assumptionthat light propagation is determined primarily by absorbance due toLambert-Beer's law neglecting multiple scattering effects in biologicaltissues. In practice, however, the optical paths of differentwavelengths in biological tissues are known to vary more in reflectanceoximetry compared to transmission oximetry, since they strongly dependon the light scattering properties of the illuminated tissue and sensormounting.

[0009] The relevant in vivo studies are disclosed, for example, in thefollowing publications:

[0010] Dassel, et al., “Effect of location of the sensor on reflectancepulse oximetry”, British Journal of Obstetrics and Gynecology, vol. 104,pp. 910-916, (1997);

[0011] Dassel, et al., “Reflectance pulse oximetry at the forehead ofnewborns: The influence of varying pressure on the probe”, Journal ofClinical Monitoring, vol. 12, pp. 421-428, (1996).

[0012] It should be understood that the signal-to-noise ratioimprovement is also needed in tissue simulated model measurements (invitro). The problems arising with in vitro measurements are disclosed,for example in the following publication: Edrich et al., “Fetal pulse,oximetry: influence of tissue blood content and hemoglobin concentrationin a new in-vitro model”, European Journal of Obstetrics and Gynecologyand Reproductive Biology, vol. 72, suppl. 1, pp. S29-S34, (1997).

[0013] Improved sensors for application in dual-wavelength reflectancepulse oximetry have been developed, and are disclosed, for example, inthe following publication: Mendelson, et al., “Noninvasive pulseoximetry utilizing skin reflectance photoplethysmography”, IEEETransactions on Biomedical Engineering, vol. 35, no. 10, pp. 798-805(1988). According to this technique, the total amount of backscatteredlight that can be detected by a reflectance sensor is directlyproportional to the number of photodetectors placed around the LEDs.Additional improvements in signal-to-noise ratio were achieved byincreasing the active area of the photodetector and optimizing theseparation distance between the light sources and photodetectors.

[0014] A different approach, based on the use of a sensor having sixphotodiodes arranged symmetrically around the LEDs, is disclosed in thefollowing publications:

[0015] Mendelson, et al., “Design and evaluation of a new reflectancepulse oximeter sensor”, Medical Instrumentation, vol. 22, no. 4, pp.167-173 (1988); and

[0016] Mendelson, et al., “Skin reflectance pulse oximetry: in vivomeasurements from the forearm and calf”, Journal of Clinical Monitoring,vol. 7, pp. 7-12, (1991).

[0017] According to this approach, in order to maximize the fraction ofbackscattered light collected by the sensor, the currents from all sixphotodiodes are summed electronically by internal circuitry in the pulseoximeter. This configuration essentially creates a large areaphotodetector made of six discrete photodiodes connected in parallel toproduce a single current that is proportiorial to the amount of lightbackscattered from the skin.

[0018] A reflectance sensor based on the use of eight dual-wavelengthLEDs and a single photodiode is disclosed in the following publication:Takatani et al., “Experimental and clinical evaluation of a noninvasivereflectance pulse oximeter sensor”, Journal of Clinical Monitoring, vol.8, pp. 257-266 (1992). Here, four R and four IR LEDs are spaced at90-degree intervals around the substrate and at an equal radial distancefrom the photodiode. A similar sensor configuration based on sixphotodetectors mounted in the center of the sensor around the LEDs isdisclosed in the following publication: Konig, et al., “Reflectancepulse oximetry—principles and obstetric application in the Zurichsystem”, Journal of Clinical Monitoring, vol. 14, pp. 403-412 (1998).

[0019] Pulse oximeter probes of the type comprising three or more LEDsfor filtering noise and monitoring other functions, such ascarboxyhemoglobin or various indicator dyes injected into the bloodstream, have been developed and are disclosed, for example, in WO00/32099 and U.S. Pat. No. 5,842,981. The techniques disclosed in thesepublications are aimed at providing an improved method for directdigital signal formation from input signals produced by the sensor andfor filtering noise.

[0020] As indicated above, in pulse oximetry, SpO₂ and the heart rateare calculated from the detected signal, which is relatively small witha reflection-mode pulse oximeter. Methods for processing the signalsdetected by a pulse oximeter are described in the following U.S. Pat.Nos. 5,482,036; 5,490,505; 5,685,299; 5,632,272; 5,769,785; 6,036,642;6,081,735; 6,067,462; and 6,083,172. These methods, however, utilize aspecific model based on certain assumptions of noise reference.

SUMMARY

[0021] There is a need in the art to improve the signal-to-noise ratio(SNR) in measured data by providing a novel method for processing ameasured signal, which has certain known characteristics.

[0022] The present invention is associated with the fact that thecharacteristics of most physiological signals are known, being forexample periodic with certain well-defined peak-to-peak intensity value(such as a pulsatile blood-related signal), or periodic with a specificasymmetric shape (such as blood pressure pulse or ECG). On the contrary,a noise component in the measured signal is typically associated withartifacts of various kinds, and therefore has no specificcharacteristics.

[0023] The main idea of the present invention is as follows. The timevariation of a response (measured signal or measured data) of a sampleto the application of an external field is detected by any suitablemeans and a measured signal representative of the response is generated.If a signal component in the measured signal is a periodic signal with acertain well-defined peak-to-peak intensity value, upper and lowerenvelopes of the measured signal are determined and analyzed to extractsaid signal component of the measured signal. This signal component canfurther be used to calculate a desired parameter of the sample. The DCcomponent of the signal is determined as the median value of the upperenvelope, and the AC component is determined as the median value of thedifference between the upper and lower envelopes. If a signal componentof the measured signal is a periodic signal characterized by a specificasymmetric shape, a specific adaptive filtering is applied to themeasured signal, resulting in the enhancement of the signal componentrelative to a noise component. This adaptive filtering is based on aderivative of the Gaussian Kernel having specific parameters matchingthe characteristics of the signal component.

[0024] The term “measured signal” used herein signifies a signalobtained by any measurement device and including a signal component,which is to be extracted and further used for determining a desiredparameter, and a noise component caused by various noise and artifactconditions. The term “measured data” used herein refers to dataindicative of two measured signals of different kinds. One kind of ameasured signal suitable to be processed by the technique of the presentinvention is such containing a signal component in the form of aperiodic signal with well-defined peak-to-peak value, e.g.,sinusoidal-like signal. The other kind of a measured signal suitable tobe processed by the technique of the present invention is one containinga signal component in the form of a periodic signal characterized by aspecific asymmetric shape. Such a periodic asymmetrically shaped signalis characterized by the following: each cycle (period) of the signalcontains a region including frequencies higher than those of the otherregions. The present invention consists of a signal processing techniquethat can be carried out by a corresponding data processing and analyzingutility incorporated in a control unit of the measurement device, or ina separate unit connectable to the measurement device to receive andprocess the output thereof

[0025] There is thus provided, according to one broad aspect of thepresent invention, a method for processing a measured signal to extracta signal component and suppress a noise component of the measuredsignal, wherein the signal component is a substantially periodic signalcharacterized by a substantially well-defined peak-to-peak intensityvalue, the method comprising the steps of:

[0026] (i) determining upper and lower envelopes of the measured signal;and

[0027] (ii) analyzing the upper and lower envelope values to extractsaid signal component from the measured signal.

[0028] The analysis of the upper and lower envelope values comprisesdetermining of a median of the difference between the upper and lowerenvelope values, as an alternating value in the signal component, and amedian of the upper envelope (or a median of the upper envelope plus thelower envelope divided by two) as a constant value in the signalcomponent. The measured signal may be a physiological signal, such as apulsatile blood-related signal, in which case the extracted signalcomponent is further used to determine a desired physiologicalparameter, such as oxyhemoglobin saturation.

[0029] The measured signal can be determined as a response of a sampleto an external field, for example, a light response of the sample toincident radiation.

[0030] According to another aspect of the present invention, there isprovided a signal processing method for use in determining a desiredparameter of a sample, the method comprising the steps of:

[0031] providing a measured signal representative of a response of saidsample to an external field, the measured signal comprising a signalcomponent indicative of said desired parameter, and a noise component,said signal component being a substantially periodic signalcharacterized by a substantially well-defined peak-to-peak intensityvalue;

[0032] determining upper and lower envelopes of the measured signal; and

[0033] analyzing the upper and lower envelope values to extract saidsignal component from the measured signal.

[0034] The providing of said measured signal may comprise sampling andfrequency filtering of said response.

[0035] According to yet another aspect of the present invention, thereis provided a method for processing a measured signal to enhance asignal component relative to a noise component in the measured signal,wherein the signal component is characterized by a specific asymmetricshape, the method comprising the steps of:

[0036] defining a kernel function being a derivative of a Gaussian withparameters matching the characteristics of said signal component; and

[0037] applying filtering to the measured signal with said kernelfunction parameters, thereby enhancing the signal component relative tothe noise component in the filtered measured signal.

[0038] According to yet another aspect of the present invention, thereis provided a computer program storage device readable by a machine,tangibly embodying a program of instructions executable by a machine toperform method steps of processing a measured signal to extract a signalcomponent and suppress a noise component of the measured signal, whereinthe signal component is a substantially periodic signal characterized bya substantially well-defined peak-to-peak intensity value, which methodcomprises the steps of:

[0039] (i) determining upper and lower envelopes of the measured signal;and

[0040] (ii) analyzing the upper and lower envelope values to extractsaid signal component from the measured signal.

[0041] According to yet another aspect of the present invention, thereis provided a computer program storage device readable by a machine,tangibly embodying a program of instructions executable by a machine toperform method steps of processing a measured signal to enhance a signalcomponent relative to a noise component in the measured signal, whereinthe signal component is characterized by a specific asymmetric shape,which method comprises the steps of:

[0042] defining a kernel function being a derivative of a Gaussian withparameters matching the characteristics of said signal component; and

[0043] applying filtering to the measured signal with said kernelfunction parameters, thereby enhancing the signal component relative tothe noise component in the filtered measured signal.

[0044] The present invention, according to yet another aspects thereof,provides a control unit to be used with a measurement device and beingpreprogrammed to carry out the method of the present invention, ameasurement system to be applied to a sample or medium to determine adesired parameter thereof by carrying out a method of the presentinvention, and a pulse oximeter utilizing such a control unit fornon-invasive measurement of blood-related parameters.

[0045] More specifically, the present invention is used in non-invasivemeasurements of blood parameters and is therefore described below withrespect to this application. It should, however, be understood that thepresent invention presents a method and utility for signal processingsuitable for use in various applications (e.g., in vivo or in vitromeasurements in a biological sample), provided that the signal componentto be extracted from the measured signal for further analysis is eithera substantially periodic signal with a well-defined peak-to-peak value,or a substantially periodic signal characterized by a specificasymmetric shape as defined above.

BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Other advantages of the present invention will be readilyappreciated as the same becomes better understood by reference to thefollowing detailed description when considered in connection with theaccompanying drawings wherein:

[0047] In order to understand the invention and to see how it may becarried out in practice, a preferred embodiment will now be described,by way of non-limiting example only, with reference to the accompanyingdrawings, in which:

[0048]FIGS. 1A and 1B illustrate a block diagram and a flow chart ofmain operation steps, respectively, of a control unit according to theinvention;

[0049]FIGS. 1C and 1D illustrate block diagrams of pulse oximetry andbio-impedance based systems, respectively, utilizing the presentinvention;

[0050]FIGS. 1E and 1F illustrate the main operational steps of a methodaccording to the invention carried out by the systems of FIGS. 1C and1D, respectively;

[0051]FIGS. 2A and 2B illustrate experimental results of the methodaccording to the invention used with the pulse oximetry, wherein FIG. 2Ashows the envelope detection technique, and FIG. 2B shows how thistechnique can be used to extract the pulse amplitude (AC) from thedetected signal;

[0052] FIGS. 3A-3B and 4A-4B illustrate, respectively, two more examplesshowing experimental results of the method according to the inventionused with the pulse oximetry;

[0053]FIGS. 5A and 5B illustrate experimental results of the methodaccording to the invention used with the bio-impedance technique,wherein FIG. 5A shows the envelope detection technique, and FIG. 5Bshows how this technique can be used to extract the pulse amplitude (AC)from the detected signal;

[0054] FIGS. 6A-6B, 7A-7B, 8A-8B and 9A-9B illustrate, respectively,four more examples showing experimental results of the method accordingto the invention used with the bio-impedance technique;

[0055]FIG. 10 illustrates the determination of a DC component of thepulsatile signal according to the invented method, as compared to thatof the conventional technique;

[0056]FIG. 11 illustrates the typical shape and timing of a bloodpressure pulse in an artery;

[0057]FIG. 12 illustrates the kernel function to be used in a methodaccording to the invention;

[0058]FIGS. 13A and 13B illustrate the experimental results of applyinga reflectance pulse oximeter to the patient's chest, presenting ameasured signal, respectively, prior to and after the filtering with thekernel function parameters;

[0059]FIGS. 14A and 14B illustrate the spectra of a measured signal,respectively, prior to and after the filtering with DG Kernelparameters; and

[0060]FIGS. 15A and 15B illustrate how the technique of the presentinvention can be used for enhancement of QRS segment in the ECG signal.

[0061] With reference to the FIGS. 1A and 1B, and in operation, thepresent invention provides a method and device for processing a measuredsignal. More specifically, the present invention extracts a signalcomponent from the noise component and suppresses a noise component.

[0062] A control unit, generally designated 1, constructed and operatedaccording to the invention for processing an input signal IS coming froma measurement device comprises a data processing and analyzing utility 2having two software modules (components) C₁ and C₂ operating together toextract or enhance a signal component and suppress a noise componentcontained in the input signal. The software component C, processes theinput signal, and the software component C₂ analyzes the processed datato either extract or enhance the signal component.

[0063] As shown in FIG. 1B, when a signal component S₁ in the form of aperiodic signal with well-defined peak-to-peak value, e.g.,sinusoidal-like signal, is to be extracted from the input measuredsignal IS, the processing of the measured signal includes determinationof upper and lower envelopes E_(up) and E_(low) thereof (step 4), whichare then analyzed to extract this signal component S₁ from a noisecomponent (step 6).

[0064] If a signal component to be enhanced relative to a noisecomponent is a periodic signal characterized by a specific asymmetricshape (i.e., each cycle (period) of the signal component contains aregion including frequencies higher than those of the other regions),the data processing and analyzing utility 2 operates to define aspecific kernel function (a derivative of a Gaussian with parametersmatching the characteristics of the asymmetrically shaped signalcomponent), and apply filtering to the measured signal with these kernelfunction parameters, thereby enhancing the signal component relative tothe noise component in the filtered measured signal.

[0065] Referring to FIG. 1C, the present invention will now be describedin the context of a measurement system 10 for non-invasive measurementof physiological parameters. It should be understood that theapplication of the present invention to such a measurement system 10 isfor discussion purposes only and the present invention is not limited tosuch applications. The present invention has equal application to otheruses where signal component of the kind specified is to be extractedfrom a measured containing a noise component.

[0066] In the present example, the system 10 is a reflectance pulseoximeter applied to a measurement location (not shown) on the patient'sbody and operable to detect a light response (reflection) of themeasurement location and determine oxyhemoglobin saturation in thepatient's blood and the heart rate. The system 10 comprises such mainconstructional parts as a measurement device 12 (probe) and a controlunit 13.

[0067] The measurement device 12 comprises an illuminator and a detectorunit. In the present example, the illuminator is composed of three lightemitting elements (e.g., LEDs) 14A, 14B and 14C operated by threedrivers D1-D3, respectively. LEDs 14A-14C illuminate the measurementlocation with three different wavelengths: one wavelength λ1 lying inthe red spectrum and the two other wavelengths λ2 and λ3 lying in aspectrum range including near infrared and infrared spectrum ofradiation. Wavelengths λ2 and λ3 are selected to coincide with aspectral region of the optical absorption curve, where oxyhemoglobin(HbO₂) absorbs slightly more light than deoxyhemoglobin (Hb), and wherethe extinction coefficients of Hb and HbO₂ are nearly equal and remainrelatively constant as a function of wavelength. The detector unitcomprises two photo-detectors PD₁ and PD₂, which receive lightcomponents reflected from the measurement location and generate measureddata (current) indicative thereof

[0068] It should be noted, although not specifically shown, that thephoto-detectors 14A,14B,14C are preferably designed and arranged so asto provide collection of light reflected from the measurement locationat different detection points arranged along closed paths around thelight emitting elements. For example, the photodetectors are twoconcentric rings (the so-called “near” and “far” rings), and the lightemitting elements are located at the center of the rings. Thisarrangement enables optimal positioning of the detectors for highquality measurements, and enables distinguishing between photodetectorsreceiving “good” information (i.e., AC and DC values which would resultin accurate calculations of SpO₂) and “bad” information (i.e., AC and DCvalues which would result in inaccurate calculations of SpO₂).

[0069] The operation of the measurement device and calculation of ablood parameter (e.g., oxyhemoglobin saturation) do not form part of thepresent invention, and therefore need not be specifically described,except to note the following. In this specific example of threewavelengths of incident radiation and a plurality of detection points,data indicative of AC/DC ratio in the light detected at each of thedetection points for the three wavelengths is calculated, and analyzedto determine accepted detection points and select corresponding AC/DCratios for each of three wavelengths. These selected ratios are thenutilized to calculate the blood parameter. The analysis consists of thefollowing: Values of the ratio W₂/W₃ (W₂=I₂(AC)/I₂(DC) and W₃=I₃(AC)/I₃(DC), I being the intensity) for the accepted detection points inat least one closed path are calculated. Each of these values isanalyzed to determine whether it satisfies a certain predeterminedcondition (e.g., the calculated value W₂/W₃ is inside a predeterminedrange defined by a threshold value), and generate a signal indicative ofwhether the position of the probe (sensor) is to be adjusted or not. Ifthe condition is satisfied, the quality of a photoplethysmogram isanalyzed to determine whether it is acceptable or not. If the quality isacceptable, the selected ratios are analyzed to calculate ratios W₁/W₂and W₁/W₃ (wherein W₁=I₁(AC)/I₁(DC)) from the data detected in at leastone closed path, and calculate the differences ABS(W₁/W₂−W₁/W₃). Thecalculated differences are analyzed to determine whether each of thedifferences satisfies a certain predetermined condition (e.g., thecalculated difference ABS(W₁/W₂−W₁/W₃) is less than a certain thresholdvalue for determining the blood parameter if the condition is satisfied.

[0070] As further shown in FIG. 1C, outputs of the photodetectors PD₁and PD₂ are connected to analog-to-digital converters ADC₁ and ADC₂,respectively, which are connected to a micro-controller 16 to therebyenable simultaneous signal conversion by sampling the signal and bandpass filtering. By this, noise having spectral components other thenthat of the signal component is suppressed. The control unit furthercomprises a processor 17 (composed of data processing and analyzingutilities U_(1 and U) ₂) preprogrammed to carry out a signal processingaccording to the invention, and a display 18. The provision of twoutilities U_(1 and U) ₂ is aimed at determining both the SpO₂ and theheart rate, wherein SpO₂ is derived from a measured signal of the kindhaving a signal component S₁ in the form of a periodic signal withwell-defined peak-to-peak value, and the heart rate is derived from ameasured signal of the kind having a signal component characterized by aspecific asymmetric shape.

[0071] It should be understood that for the purpose of the presentinvention, the light source (with respective drivers), detector,analog-to-digital converters and micro-controller constitute together ameasurement device for generating data indicative of a measured signal,which includes a signal component and a noise component (noise andartifacts). Such a measurement device may be of any kind. Actually, theprocessor, having either one of the utilities U₁ and U₂ or both of them,may be incorporated in a separate unit connectable to the measurementdevice to receive and process the measured signal to thereby enable thedetermination of a desired parameter. For the purposes of the presentinvention, the signal component in the measured signal is a periodicsignal with a well-defined peak-to-peak value (e.g., a pulse relatedsignal of blood), or a signal with a specific asymmetric shape (e.g., aheart pulse signal). By using the reflectance pulse oximeter 10 appliedto a location on the patient's body, the measured data contains both thesignal component S₁ representative of the pulse related signal of thepatient's blood (a substantially periodic signal with substantiallywell-defined peak-to-peak intensity value) and the signal component S₂representative of the pulse related signal of the heart (a periodicsignal characterized by a specific asymmetric shape).

[0072]FIG. 1D illustrates a block diagram of a measurement system 100for bio-impedance measurements. To facilitate understanding, the samereference numbers are used to identify those components that are commonin the examples of FIGS. 1C and 1D. Thus, the measurement system 100 iscomposed of a measurement device 12 and a control unit 13, whichcomprises a processor 17 (composed of data processing ad analyzingutilities U₁ and U₂) preprogrammed for carrying out the method accordingto the invention. In the present example of FIG. 1D, the measurementdevice 12 comprises an alternating current source 114 operated by themicro-controller 16.to inject an electric current to the patient's bodyby stimulating body electrodes 115; electrodes 116 sensitive to voltageinduced by the injected alternating current; and electronic components117 (demodulators and amplifiers) for detecting and amplifying theamplitude of the alternating voltage received from the sensingelectrodes 116. In the measurement device of this kind, differentelectrodes' arrangements are typically used for producing thebio-impedance and ECG measured signals MS₁ and MS₂.

[0073] Reference is made to FIGS. 1E and 1F, illustrating the principlesof the method according to the invention in the pulse oximeter andbio-impedance applications, respectively. To facilitate understanding,the same reference numbers are used to identify steps that are common inthe examples of FIGS. 1E and 1F.

[0074] As shown, measured data MD received from a measurement devicefirst undergoes sampling and frequency filtering. In the example of FIG.1E (pulse oximetry), the measured data MD, indicative of a pulsatileblood-related signal including both the periodic signal component withwell-defined peak-to-peak intensity value and the periodic signalcomponent characterized by a specific asymmetric shape, is supplied fromthe measurement device of a pulse oximeter, sampled (step 20), and thenundergoes frequency filtering (step 22). The measured data MD is thensplit so as to undergo two concurrent processes carried out byrespective data processing and analyzing utilities: a processing todetermine the upper and lower envelopes of the measured data MD (step26), and filtering of the measured data MD with a specific DG Kernel, aswill be described more specifically further below.

[0075] In the example of FIG. 1F, measured signals MS₁ and MS₂(indicative of, respectively, a bio-impedance and an ECG) are suppliedfrom different electrode arrangements of the measurement device.Consequently, the measured signals are sampled by separate samplingutilities (steps 20A and 20B). Data indicative of the sampled measuredsignal MS, undergoes frequency filtering (step 22), and data indicativeof the sampled measured signal MS₂ undergoes DG kernel filtering (step24). The frequency-filtered measured signals MS₁ is processed tocalculate upper and lower envelopes thereof (step 26).

[0076] The upper and lower envelopes are used to determine AC and DCcomponents of a pulsatile blood-related signal component of the measuredsignal (steps 28 and 30). The so-determined AC and DC components areused to calculate oxyhemoglobin saturation SpO₂ (step 32 in FIG. 1E), orthe normalized impedance Z=AC/DC (step 33 in FIG. 1F), and thecalculation results are then displayed (step 34). The DG Kernel filtereddata is processed to calculate the spectrum (step 36), which is analyzedto determine the biggest peak which is the heart rate (step 38). Thecalculation results are presented on the display (step 40).

[0077] Reference is made to FIGS. 2A-2B, 3A-3B and 4A-4B illustratingthree examples, respectively, of processing a measured signal obtainedwith a pulse oximeter. FIGS. 2A, 3A and 4A illustrate the sampled andfrequency filtered measured signals MS⁽¹⁾ ₁, MS⁽²⁾ ₁ and MS⁽³⁾ ₁ (eachhaving a signal component representative of a pulsatile blood-relatedsignal distorted by motion and respiration artifacts (noise component)),and upper and lower envelopes E⁽¹⁾ _(up) and E⁽¹⁾ _(low), E⁽²⁾ _(up) andE⁽²⁾ _(low) and E⁽³⁾ _(up) and E⁽³⁾ _(low) of the measured signals MS⁽¹⁾₁, MS⁽²⁾ ₁ and MS(³⁾ ₁, respectively. As shown in the example of FIG.2A, the amplitude of the artifacts is about 6 times larger than thepulse amplitude (AC).

[0078] In order to calculate the upper and lower envelopes of a signal,the location of the local maximum and minimum values of the periodicsignal are first calculated. Then, the values between the local minimumpoints are estimated producing a continuous line that defines the lowerenvelope, and the values between the local maximum points are estimatedproducing a continuous line that defines the upper envelope. The lineestimation between extreme points can for example utilize linearinterpolation or cubic spline interpolation methods.

[0079]FIGS. 2B, 3B and 4B illustrate (in the enlarged scale) a signalresulting from the subtraction of the upper envelope from the respectivemeasured signal (determination of the difference between the intensityvalues of the measured signal and the upper envelope for each point intime). As seen, distortions are now smaller than the signal amplitude,and hence, the signal-to-noise ratio is improved (by a factor of 10 inthe example of FIGS. 2A-2B).

[0080] In order to calculate the amplitude of the blood pulsation (ACcomponent of the pulsatile blood-related signal), the lower envelopevalue is subtracted from the upper envelope value (E_(up)−E_(low)) foreach time moment, thereby obtaining a vector of the same length as thevector representing the measured signal. Then, the vector values aresorted, and the median is calculated. Thus, according to the presentinvention, the alternating value (AC component) of a periodic signalwith well-defined peak-to-peak intensity value is calculated as:

AC=MEDIAN(E _(up) −E _(low))

[0081] It should be noted that, according to conventional techniques,extreme points are used to calculate the pulse amplitude. Hence, for aframe of 256 points (about 3 sec), 3 heartbeats are observed (assuming aheart rate of 60 beats per minute), namely, only 3 maximal and 3 minimalvalues (one for each pulse). The calculation of the amplitudes of 3pulses in the 3 sec frame enables to obtain only 3 numbers, and the meanamplitude in the frame is calculated from these 3 pulse amplitudes. Ifthe detected signal includes data representative of an additional pulsethat does not really exist, this will affect the data analysis results(one wrong amplitude number from three values: two correct values andone false).

[0082] On the contrary, the present invention utilizes the statisticalanalysis of 256 values obtained after the subtraction of the twoenvelopes to estimate the most likely to appear amplitude in the frame.In order to reduce the influence of artifacts and to find the median ofthe signal (i.e., amplitude value that is most likely to appear)resulted from the subtraction (E_(up−E) _(low)), the values are sorted,10% of the extreme values (the smallest and the largest ones) areexcluded, and the median is taken from the remaining values.

[0083] FIGS. 5A-5B, 6A-6B, 7A-7B, 8A-8B and 9A-9B illustrate fivedifferent examples, respectively, of processing a measured signalobtained with bio-impedance measurements of heart activity in a cardiacoutput measurement device. Here, FIGS. 5A, 6A, 7A, 8A and 9A show thesampled and frequency filtered measured signals (each having a signalcomponent representative of a pulsatile blood-related signal distortedby motion and respiration artifacts), and upper and lower envelopes ofthe measured signals. FIGS. 5B, 6B, 7B, 8B and 9B signals with theimproved signal-to-noise ratio obtained by subtracting the upperenvelopes from the respective measured signals.

[0084] Calculation of the DC component of a blood-related signalcontained in the measured signal MS₁ will now be described withreference to FIG. 10. When illuminating the measurement location duringthe pulse (when blood fills a blood vessel), more of the incident lightis absorbed. Therefore, the detected signal reflected from the skin isdecreased accordingly (proportional to the light absorption).

[0085] According to the conventional approach, the constant value of thereflected light intensity (i.e., the DC component of thephotoplethysmogram) is calculated as the average value of a signal S₁measured in the middle of the measured signal MS₁. This approach isbased on the fact that the average value contains the constant level ofreflected light (between arterial pulses) and the pulsation value (ACcomponent). This averaging value is a result of the base line, theamplitude of the pulse, and the shape of the pulse.

[0086] According to the technique of the present invention, the realconstant absorption component defined by the upper envelope E_(up) ofthe measured signal MS₁ is used to calculate the DC component value,which gives better accuracy, as compared to the conventional approach.Thus, according to the invention, the upper envelope values are sorted,and the median is taken as the DC component, i.e., DC=MEDIAN(E_(up)).Alternatively, the DC component of such a periodic signal withwell-defined peak-to-peak value may be calculated as the median of thehalf of the sum of the upper and lower envelope values, i.e.,DC=MEDIAN((E_(up)+E_(low))/2).

[0087] The signal processing according to the invention suitable to beused for the calculation of the heart rate will now be described. Thistechnique is based on the knowledge about the physiological propertiesof the biophysical signals related to the heart cycle, and consists of aspectral filtering kernel preprocessing in order to enhance the pulsesignal from the additive noise and disturbances, thus improving thesignal-to-noise ratio. This makes further processing techniques, such asFast Fourier Transform and auto correlation, more efficient whenprocessing the signal to calculate the heart rate.

[0088]FIG. 11 illustrates a graph G of the typical shape and timing ofthe blood pressure pulse in an artery which represents a biophysicalsignal related to the change in the blood pressure, induced by the heartcycle, and presents a signal component in the measured signal MS₂. Thissignal component has the active phase (systolic phase) P_(act) and thepassive phase (diastolic phase) P_(pas) of the pulse. The duration ofthe active phase Pact is defined by the heart's contraction phase andranges between 80 and 140 ms, and the duration of the passive phaseP_(pas) is the remaining time, i.e., the difference between the heartrate duration and the active phase duration. The typical human heartrate ranges between 40 bpm and 280 bpm, and is equivalent to thefrequency range of 0.67-4.7 Hz. In order to filter out noise andartifacts, the pulse oximeter, as well as any other suitable measurementdevice, typically utilizes filters with the band pass of 0.5-10 HZ.Examining the frequency content of the systolic phase P_(act) in theheart pulse, it is evident that it contains frequencies above 10 Hz. Forexample, in a 80 ms rising phase, the frequency content of 12.5 HZ isincluded (i.e., 1/0.08=12.5).

[0089] In order to enhance the heart pulse signal, the present inventionutilizes the specific asymmetric shape of the blood pressure pulse byadapting the filtering to the fast rising phase of the signal, andthereby distinguishing the pulse signal component from the noisecomponent in the measured signal MS₂. In order to prevent disruption ofthe fast rising phase, the pass band of such an adaptive filter has toinclude frequencies above 12.5 Hz. As for the lower bound, 0.5 Hz is aproper cut-off frequency, since the heart rate goes down to thefrequency of 0.67 Hz, and below this value just a slow artifact takesplace, being caused by respiration or motion.

[0090] To this end, a special DG Kernel is used based on an analyticfunction in the form of the Derivative of a Gaussian (DG). The DG Kernel(DGK) analytic equation is:${{DGK}(t)} = {\frac{- t}{\sigma \sqrt{2\pi \quad \sigma^{2}}}\exp \left\lfloor {{- \frac{1}{2\sigma}}t^{2}} \right\rfloor}$

[0091] wherein t and σ are the time and Gaussian width parameters. Theseparameters of the DG Kernel function should be matched to the pulsecharacteristics in order to have the best SNR.

[0092]FIG. 12 illustrates the function DGK(t). This kind of kernel canadvantageously function as a low pass filter to thereby filter highfrequency noise. Additionally, this kernel can enhance the signalcomponent in the measured signal when the signal component includes fastslopes at a specific range. This is due to the fact that the derivativeoperation of the filter is limited to its pass band region. One passoperation of filtering and heart pulse enhancement allow for real timefast determination of the heart rate.

[0093] The parameters of this kernel can be adjusted to enhance thesystolic phase of the heart pulse signal or even of the QRS segment inan ECG signal, since the frequency content of the QRS segment includesfrequencies higher then the frequencies in other segments of the ECGsignal. Irrespective of that the shape of the ECG signal is differentfrom the shape of the heart pulse, the DGK can be adapted to enhance theQRS segment relative to other segments in the ECG and to noise andartifacts contained in the ECG measured signal. This technique assistsin the detection of the QRS segment, as will be described morespecifically further below. Due to the fact that the signal processingaccording to the invention utilizes the asymmetric property of the pulsesignal distinguishing it from other components (noise and artifacts) inthe measured signal, the improved signal-to-noise ratio can be obtained,even when the noise and artifact frequency content overlaps with theheart rate frequency.

[0094] Thus, the present invention utilizes the Gaussian analyticequation, calculation of the analytic derivative, digitization at therelevant signal sampling frequency, optimization of the length t of theKernel and the Gaussian width σ for the best performance, and thenutilizes the result parameters as a general Finite Impulse Response(FIR) filter parameter. After filtering the measured signal MS₂ with theDG Kernel parameters, the energy in the measured signal related to thepulse is enhanced in relation to other artifacts and noise. The generalFast Fourier Transform can then be used to extract the heart rate.

[0095]FIGS. 13A and 13B illustrate the experimental results of applyinga reflectance pulse oximeter to the patient's chest. FIG. 13A shows agraph H₁ presenting the measured signal MS₂. Here, respiration and othermotion disturbances are presented as relatively slow changes in thesignal base line. Heart signals are relatively fast and characterized byperiodic small changes in the signal amplitude. It is evident thatartifacts are dominant over the heart pulses, as they are about three tofour times larger. FIG. 13B illustrates a graph H₂ presenting the resultof the filtering of the measured signal of FIG. 13A with the DG Kernelparameters. Here, the heart pulses are dominant. Although the pulseamplitudes are modulated by the artifacts' trend, signal-to-noise ratiois significantly improved. As shown, small pulses that were distorted inthe signal of FIG. 13A by the artifacts, have proper amplitudes in thesignal of FIG. 13B.

[0096]FIGS. 14A and 14B illustrate the spectra S₁ and S₂ of the measuredsignal containing an asymmetrically shaped signal component,respectively, prior to and after the filtering with DG Kernelparameters. Comparing these spectra to each other, it is clear that thepeak representing the heart rate at 2.2 Hz in much larger than theartifact peaks after the DG Kernel filtering. In other words, the DGKernel filtering results in the enhancement of the heart rate peak atabout 2.2.Hz relative to other double peaks.

[0097] Many medical procedures require detection of the QRS segment ofthe ECG signal. The use of DG Kernel parameters for filtering enablesenhancement of the QRS segment relative to other segments in the ECGsignal. FIGS. 15A and 15B illustrate respectively, the typical ECGsignal with QRS segment, respectively prior to and after the filteringwith the DG Kernel method, showing that the QRS segments are enhanced inthe filtered signal.

[0098] Turning back to FIGS. 1E and 1F, the DG Kernel method is appliedto the measured signal after being frequency-filtered to suppress noisehaving a frequency other than that of the heart pulse signal. In otherwords, DG Kernel filtering is applied to the signal in which the noiseand artifacts frequency spectra overlap the heart rate frequencyspectrum. By this, pulse related information is enhanced, and then ageneral spectrum method can be applied to obtain the heart rate. TheSpO₂ level is calculated using the envelope technique: The median of thedifference (E_(up)−E_(low)) between the upper and lower envelope valuesis used for the pulse amplitude calculation (AC component of thepulsatile blood-related signal). The median of the upper envelope E_(up)is used for the calculation of the constant detected light (DC componentof the pulsatile blood-related signal). The so-obtained AC and DCcomponents are utilized to extract SpO₂ according to any suitableconventional technique.

[0099] Those skilled in the art will readily appreciate that variousmodifications and changes can be applied to the embodiments of theinvention as hereinbefore exemplified without departing from its scopeas defined in and by the appended claims.

What is claimed is:
 1. A method for processing a measured signal toextract a signal component and suppress a noise component of themeasured signal, wherein the signal component is a substantiallyperiodic signal characterized by a substantially well-definedpeak-to-peak intensity value, the method comprising the steps of (i)determining upper and lower envelopes of the measured signal; and (ii)analyzing the upper and lower envelope values to extract the signalcomponent from the measured signal.
 2. The method, as set forth in claim1, wherein the step analyzing the upper and lower envelope valuesincludes the step of determining a median of the difference between theupper and lower envelope values, as an alternating value in the signalcomponent.
 3. The method, as set forth in claim 1, wherein the step ofanalyzing the upper and lower envelope values includes the step ofdetermining a median of the upper envelope values, as a constant valuein the signal component.
 4. The method, as set forth in claim 1, whereinthe step of analyzing the upper and lower envelope values includes thestep of determining a median of the half of the sum of the upper andlower envelope values, as a constant value in the signal component. 5.The method, as set forth in claim 1, wherein the measured signal is aphysiological signal.
 6. The method, as set forth in claim 5, whereinthe signal component is pulsatile blood-related signal.
 7. The method,as set forth in claim 6, wherein the pulsatile blood-related signal isindicative of oxyhemoglobin saturation level.
 8. The method, as setforth in claim 7, wherein the step of analyzing the upper and lowerenvelope values includes the step of determining a median of thedifference between the upper and lower envelope values as an ACcomponent of the pulsatile blood-related signal, and determining amedian of the upper envelope values as a DC component of the pulsatileblood-related signal.
 9. The method, as set forth in claim 7, whereinthe step of analyzing the upper and lower envelope values includes thestep of determining a median of the difference between the upper andlower envelope values as an AC component of the pulsatile blood-relatedsignal, and determining a median of a half of the sum of the upper andlower envelope values as a DC component of the pulsatile blood-relatedsignal.
 10. The method, as set forth in claim 1, wherein the measuredsignal is a response of a sample to the application of an externalfield.
 11. The method, as set forth in claim 10, wherein the measuredsignal is a light response of the sample to incident light.
 12. Themethod, as set forth in claim 10, wherein the sample is biological. 13.The method, as set forth in claim 1, for use with a measurement devicefor non-invasive measurements of patient's blood and heart conditions,the signal component being a pulsatile blood-related signal andcontaining a signal component characterized by a specific asymmetricshape, the method further comprising the steps of: defining a kernelfunction being a derivative of a Gaussian with parameters matching thecharacteristics of the signal component with the asymmetric shape; andapplying spectral filtering to the measured signal with the kernelfunction, thereby enhancing the signal component characterized by thespecific asymmetric shape relative to a noise component in the filteredsignal, to thereby enable further processing of the enhanced pulsesignal to determine the heart rate.
 14. The method, as set forth inclaim 13, wherein the step of analyzing the upper and lower envelopevalues includes the steps of determining a median of the differencebetween the upper and lower envelope values of the measured signal as anAC component of the pulsatile blood-related signal component, anddetermining a median of the upper envelope values as a DC component ofthe pulsatile blood-related signal component.
 15. The method, as setforth in claim 13, wherein the step of analyzing the upper and lowerenvelope values includes the steps of determining a median of thedifference between the upper and lower envelope values of the measuredsignal as an AC component of the pulsatile blood-related signalcomponent, and determining a median of a half of the sum of the upperand lower envelope values as a DC component of the pulsatileblood-related signal component.
 16. A signal processing method for usein determination of a desired parameter of a sample, the methodcomprising the steps of: providing a measured signal representative of aresponse of the sample to an external field, the measured signalcomprising a signal component indicative of the desired parameter, and anoise component, the signal component being a substantially periodicsignal characterized by a substantially well-defined peak-to-peakintensity value; determining upper and lower envelopes of the measuredsignal; and analyzing the upper and lower envelope values to extract thesignal component from the measured signal, to enable further processingof the extracted signal component to determine the desired parameter.17. The method, as set forth in claim 16, wherein the step of providingthe measured signal includes the step of sampling and frequencyfiltering of the response.
 18. A method for processing a measured signalto enhance a signal component relative to a noise component in themeasured signal, wherein the signal component is a characterized by aspecific asymmetric shape, the method comprising the steps of: defininga kernel function being a derivative of a Gaussian with parametersmatching the characteristics of the signal component; and applyingspectral filtering to the measured signal with the kernel function,thereby enhancing the signal component relative to the noise componentin the filtered measured signal.
 19. A method for processing a measuredsignal including a first signal component in the-form of a substantiallyperiodic signal with substantially well-defined peak-to-peak intensityvalue, and a second signal component characterized by a specificasymmetric shape, to extract the signal components from noisecomponents, the method comprising the steps of: processing the measuredsignal by determining upper and lower envelopes thereof, and analyzingthe upper and lower envelope values to extract the first signalcomponent; and defining a kernel function being a derivative of aGaussian with parameters matching characteristics of the second signalcomponent, and processing the measured signal by filtering it with thekernel function parameters, thereby enhancing the second signalcomponent relative to the noise component in the filtered measuredsignal.
 20. A method for processing measured data representative of afirst measured signal including a first signal component in the form ofa substantially periodic signal with substantially well-definedpeak-to-peak intensity value, and a second measured signal including asecond signal component characterized by a specific asymmetric shape, toextract the signal components from noise components, the methodcomprising the steps of processing the first measured signal bydetermining upper and lower envelopes thereof, and analyzing the upperand lower envelope values to extract the first signal component;defining a kernel function being a derivative of a Gaussian withparameters matching characteristics of the second signal component, andprocessing the second measured signal by filtering it with the kernelfunction parameters, thereby enhancing the second signal componentrelative to the noise component in the filtered second measured signal.21. The method, as set forth in claim 20, wherein the first signalcomponent is a pulsatile blood-related signal.
 22. The method, as setforth in claim 20, wherein said second measured signal is ECG, thesecond signal component being representative of a QRS segment in the ECGsignal.
 23. A control unit for use with a measurement device to receiveand process a measured signal generated by the measurement device so asto extract a signal component from a noise component in the measuredsignal, the signal component being a substantially periodic signal withsubstantially well-define peak-to-peak intensity value, the control unitcomprising a data processing and analyzing utility preprogrammed todetermine upper and lower envelopes of the measured signal, andanalyzing the upper and lower envelope values to extract the signalcomponent.
 24. A control unit for use with a measurement device toreceive and process a measured signal generated by the measurementdevice so as to enhance a signal component relative to a noise componentin the measured signal, the signal component being characterized by aspecific asymmetric shape, the control unit comprising a data processingand analyzing utility preprogrammed to define a kernel function being aderivative of a Gaussian with parameters matching the characteristics ofthe signal component, and apply spectral filtering to said measuredsignal with the kernel function parameters, thereby enhancing the signalcomponent relative to the noise component in the filtered measuredsignal.
 25. A pulse oximeter comprising: (a) a measurement deviceoperable to illuminate a measurement location with incident light ofpredetermined frequencies, detect a light response of the measurementlocation to said incident light, and generate a measured signalindicative thereof including a signal component representative of apulsatile blood-related signal; and (b) a control unit connectable tothe measurement device for receiving and processing the measured signal,the control unit comprising a data processing and analyzing utilitypreprogrammed to determine upper and lower envelopes of the measuredsignal, and analyze the upper and lower envelope values to extract saidpulsatile blood-related signal component from a noise component in themeasured signal.
 26. The pulse oximeter, as set forth in claim 25,wherein the analyzing of the upper and lower envelope values comprisesdetermining a median of the difference between the upper and lowerenvelope values as an AC component of the pulsatile blood-relatedsignal, and determining a median of the upper envelope values as a DCcomponent of the pulsatile blood-related signal.
 27. The pulse oximeter,as set forth in claim 25, wherein the analyzing of the upper and lowerenvelope values comprises determining a median of the difference betweenthe upper and lower envelope values as an AC component of the pulsatileblood-related signal, and determining a median of a half of the sum ofthe upper and lower envelope values as a DC component of the pulsatileblood-related signal component.
 28. The pulse oximeter, as set forth inclaim 25, for determining a patient's heart rate, the measured signalcomprising a blood-related signal component characterized by a specificasymmetric shape, the control unit being preprogrammed to process themeasured signal by filtering it with a predefined kernel function beinga derivative of a Gaussian with parameters matching the characteristicsof said signal component, thereby enhancing said signal componentcharacterized by the specific asymmetric shape relative to a noisecomponent in the filtered measured signal.
 29. A measurement system tobe applied to a sample to determine a desired parameter thereof, thesystem comprising: a measurement device operable to apply an externalfield to a measurement location on the sample or medium, detect aresponse of the measurement location to the application of the externalfield, and generate measured data indicative thereof, the measured datacontaining a first measured signal including a signal component in theform of a substantially periodic signal with a substantiallywell-defined peal-to-peak intensity value, and a second measured signalincluding a second signal component characterized by a specificasymmetric shape; and a control unit connectable to the measurementdevice for receiving and processing the measured data, the control unitcomprising data processing and analyzing preprogrammed to process thefirst measured signal by determining upper and lower envelopes thereofand analyze the upper and lower envelope values to extract the firstsignal component from a noise component in the first measured signal,and to process the second measured signal by filtering it with apredefined kernel function being a derivative of a Gaussian withparameters matching the characteristics of the second signal component,thereby enhancing the second signal component relative to a noisecomponent in the filtered measured signal.
 30. The system, as set forthin claim 29, wherein the first signal component is a pulsatileblood-related signal.
 31. The system, as set forth in claim 29, whereinthe second measured signal is ECG, the second signal component beingrepresentative of a QRS segment in the ECG signal.
 32. A computerprogram storage device readable by a machine, tangibly embodying aprogram of instructions executable by a machine to perform method stepsof processing a measured signal to extract a signal component andsuppress a noise component of the measured signal, wherein the signalcomponent is a substantially periodic signal characterized by asubstantially well-defined peak-to-peak intensity value, which methodcomprises the steps of: (i) determining upper and lower envelopes of themeasured signal; and (ii) analyzing the upper and lower envelope valuesto extract the signal component from the measured signal.
 33. A computerprogram storage device readable by a machine, tangibly embodying aprogram of instructions executable by a machine to perform method stepsof processing a measured signal to enhance a signal component relativeto a noise component in the measured signal, wherein the signalcomponent is characterized by a specific asymmetric shape, which methodcomprises the steps of defining a kernel function being a derivative ofa Gaussian with parameters matching the characteristics of the signalcomponent; and applying filtering to the measured signal with the kernelfunction parameters, thereby enhancing the signal component relative tothe noise component in the filtered measured signal.
 34. A method fordetermining a parameter of a signal, comprising: (i) determining upperand lower envelopes of the signal, and (ii) analyzing the upper andlower envelopes to extract a signal component of the signal; and, (iii)determining the parameter of the signal as a function of the signalcomponent.
 35. A method, as set for in claim 34, wherein the signalcomponent is substantially periodic.
 36. A method, as set forth in claim34, wherein the signal component has-a substantially definedpeak-to-peak intensity value.
 37. A method, as set forth in claim 34,wherein the step of analyzing the upper and lower envelopes includes thestep of suppressing noise.
 38. A method, as set forth in claim 34,including the steps of applying an external field to a sample andsensing the signal, wherein the signal is a response of the sample tothe external field.
 39. A method, as set forth in claim 34, includingthe steps of applying incident radiation to a sample and sensing thesignal, where the signal is a response of the sample to the incidentradiation.
 40. A method, as set forth in claim 39, wherein the parameterof the signal corresponds to a physiological parameter of the sample.41. A method, as set forth in claim 40, wherein the physiologicalparameter is pulsatile blood-related.
 42. A method, as set forth inclaim 40, wherein the physiological parameter is oxyhemoglobinsaturation.
 43. A method, as set forth in claim 34, wherein the step ofanalyzing the upper and lower envelopes to extract a signal component ofthe signal includes the step of determining a median of the differencebetween upper and lower envelope values.
 44. A method, as set forth inclaim 43, wherein the median is determined as an alternating value inthe signal component.
 45. A method, as set forth in claim 43, whereinthe median is determined as a constant value in the signal component.46. A method, as set forth in claim 34, wherein the step of analyzingthe upper and lower envelopes to extract a signal component of thesignal includes the steps of. determining a median difference betweenthe upper and lower envelope values as an AC component of the signalcomponent; and, determining a median of the upper envelope as a DCcomponent of the signal component.
 47. A method for determining aparameter of a signal having a signal component, including the steps of:(i) defining a kernel function as a derivative of a Gaussian withparameters matching characteristics of the signal component; and (ii)applying a spectral filter to the signal, the spectral filter using thekernel function and responsively enhancing the second signal component;and, (iii) determining a second parameter of the signal as a function ofthe enhanced second signal component.
 48. A method, as set forth inclaim 47, wherein the characteristics of the signal component are aspecific asymmetric shape.
 49. A method for determining first and secondparameters of a signal, the signal having first and second signalcomponents, comprising: (i) determining upper and lower envelopes of thesignal, and (ii) analyzing the upper and lower envelopes to extract thefirst signal component of the signal; (iii) determining the firstparameter of the signal as a function of the first signal component;(iv) defining a kernel function as a derivative of a Gaussian withparameters matching characteristics of the second signal component; and(v) applying a spectral filter to the signal, the spectral filter usingthe kernel function and responsively enhancing the second signalcomponent; and, (vi) determining a second parameter of the signal as afunction of the enhanced second signal component.
 50. An apparatus,comprising: a detector for receiving a measured signal; and, acontroller coupled to the detector and adapted to receive the measuredsignal, determine upper and lower envelopes of the measured signal,analyze the upper and lower envelopes to extract a signal component ofthe signal, and to determine a parameter of the signal as a function ofthe signal component.
 51. An apparatus, as set for in claim 50, whereinthe signal component is substantially periodic.
 52. An apparatus, as setforth in claim 50, wherein the signal component has a substantiallydefined peak-to-peak intensity value.
 53. An apparatus, as set forth inclaim 50, including an emitter to apply an external field to a sample,wherein the signal is a response of the sample to the external field.54. An apparatus, as set forth in claim 53, wherein the parameter of thesignal corresponds to a physiological parameter of the sample.
 55. Anapparatus, as set forth in claim 54, wherein the physiological parameteris pulsatile blood-related.
 56. An apparatus, as set forth in claim 54,wherein the physiological parameter is oxyhemoglobin saturation.
 57. Anapparatus, as set forth in claim 50, wherein the controller is adaptedto extract the signal component of the signal by determining a median ofthe difference between upper and lower envelope values.
 58. Anapparatus, as set forth in claim 57, wherein the median is analternating value in the signal component.
 59. An apparatus, as setforth in claim 57, wherein the median is a constant value in the signalcomponent.
 60. An apparatus, comprising: a detector for receiving ameasured signal; and, a controller coupled to the detector and adaptedto receive the measured signal, define a kernel function as a derivativeof a Gaussian with parameters matching characteristics of the signalcomponent, apply a spectral filter to the signal, the spectral filterusing the kernel function and responsively enhance the second signalcomponent, and to determine a second parameter of the signal as afunction of the enhanced second signal component.
 61. An apparatus, asset forth in claim 60, wherein the characteristics of the signalcomponent are a specific asymmetric shape.